Search results

Frequent disasters pose a significant threat to Indigenous societies, knowledge and cultures in the South Pacific. This paper will highlight the imperative to recognize and incorporate women and Indigenous knowledge in strengthening disaster risk reduction (DRR) within these societies. While existing research often emphasizes women’s vulnerability in disasters, there is a notable gap in documenting their resilience (Moreno and Shaw, 2018), particularly stemming from Indigenous women’s traditional roles and practices (Bajracharya et al., 2022).

This paper will identify the application of traditional knowledge in responding to disaster risk and early warning systems, examine traditional knowledge systems and structures in local communities and assess the contribution of Samoan women in disaster preparations.

Findings show the importance of recognizing and valuing the traditional expertise of Samoan women, providing essential insights for the development of contextually appropriate and sustainable disaster preparedness strategies.

With Samoa as the case study, this paper will employ culturally relevant Pacific research approaches to investigate women’s preparedness and response capacities to disasters.

This case study is built from secondary data such as news articles, regulations and videos. Several drafts of the case study with a teaching note were tested in the classroom setting and shared in a case writing conference. The case was revised based on feedback from students and roundtable discussions from the conference.

Mrs Hsu, the Deputy Director of the National Taxation Bureau’s Nantou County Branch in Taiwan, faced a dilemma in June 2021. One of her employees, Mrs Chiang, had requested to return to work after taking several years of parental leave since August 2017. This long absence had put a strain on colleagues, who either had to cover for her or work with temporary replacements. While Mrs Chiang’s actions were legal and protected by her government employee role, her decision to take another leave immediately after receiving a COVID-19 vaccine raised eyebrows. Her peers accused her of using her frontline worker status to gain early vaccine access and other work benefits. Mrs Hsu, upon reviewing Mrs Chiang’s employment history, pondered her next steps concerning Mrs Chiang’s new leave request.

This case would be appropriate for a course in Human Resource Management, Organizational Behavior or Gender, Family and Work, especially with the topic of Employment Rights/Legal Protections (in HR), and/or Justice and Ethics (in OB).

The purpose of this study is to explore how big data analytics (BDA) as a potential information technology (IT) innovation can facilitate the retail logistics supply chain (SC) from the perspective of outbound logistics operations in the United Kingdom. The authors' goal was to better understand how BDA can be integrated to streamline SCs and logistical networks by using the technology, organisational and environmental model.

The authors applied existing theoretical foundations for theory building based on semi-structured interviews with 15 SC and logistics managers.

The perceived benefits of using BDA in outbound retail logistics comprised the strongest predictor amongst technological, organisational and environmental issues, followed by top management support (TMS). A framework was proposed for the adoption of BDA in retail logistics. Contextual concepts from previous literature have helped us understand how environmental changes impact BDA decision-making, as such: (i) SC maturity levels and connectivity affect BDA utilisation, (ii) connected SCs improve data accessibility and information exchange, (iii) the benefits of BDAs also affect adoption and (iv) outsourcing complex tasks to experts allows companies to focus on core businesses instead of investing in IT infrastructure.

Outside the key findings listed, this study shows that there is no one-size-fits-it-all approach for use within all organisational settings. The proposed framework reveals that the perceived benefit of BDA is non-transferrable and requires top-level management support for successful implementation.

The existing literature focusses on the approaches to applying BDA in SC and logistics but fails to present a deep dive into retail outbound logistics activity. This study addresses the “how” and proposes a social-inclusive framework for a technology-enabled topic.

This study aims to explore key questions within the context of Asian countries: How do artificial intelligence (AI) and blockchain adoption in accounting influence enterprise risk management and environmental, social and governance (ESG) performance? What role does enterprise risk management have as a mediator in this relationship? In addition, how does environmental uncertainty shape the interplay between AI and blockchain adoption in accounting, enterprise risk management and ESG performance?

The authors collected data from Thomson Reuters Eikon Datastream, initially targeting the 20 Asian countries with the highest gross domestic product (GDP) per capita. Using stringent selection criteria, the research sample included 22,212 firms from these countries: Bahrain, China, Hong Kong, Indonesia, Israel, Japan, Jordan, Kazakhstan, South Korea, Kuwait, Lebanon, Malaysia, Oman, Qatar, Saudi Arabia, Singapore, Sri Lanka, Thailand, the United Arab Emirates and Vietnam. After a rigorous screening process, the final sample comprised 1,742 firms, representing 17,420 firm-year observations over the 2014–2023 period. This paper applied maximum likelihood structural equation modeling to analyze the data.

The findings reveal that both AI and blockchain adoption in accounting, along with enterprise risk management, positively impact ESG performance in the Asian context. Enterprise risk management serves as a mediating factor between AI and blockchain adoption in accounting and ESG performance. In addition, environmental uncertainty significantly moderates the relationships between AI and blockchain adoption in accounting and enterprise risk management, as well as between enterprise risk management and ESG performance.

This study uncovers the interplay between internal factors – such as AI and blockchain adoption in accounting and enterprise risk management – and external factors, notably environmental uncertainty, in fostering sustainable value for Asian firms. Internal factors enable firms to integrate ESG considerations into their operations, facilitating risk mitigation and enhancing ESG performance. Meanwhile, heightened environmental uncertainty drives the adoption of sustainable practices. Consequently, Asian Governments should prioritize the development of regions characterized by high environmental uncertainty to advance national sustainable development goals and encourage responsible business practices.

This study contributes to the existing literature by uncovering the combined effects of internal and external factors on ESG performance, offering empirical evidence from Asian countries with high GDP per capita. Specifically, it underscores the efficacy of AI and blockchain adoption in accounting and enterprise risk management, as well as the moderating role of environmental uncertainty, within the Asian context.